Gene expression profiling using flexible neural trees
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Chen, Yuehui | - |
dc.contributor.author | Peng, Lizhi | - |
dc.contributor.author | Abraham, Ajith | - |
dc.date.accessioned | 2023-03-09T00:34:48Z | - |
dc.date.available | 2023-03-09T00:34:48Z | - |
dc.date.issued | 2006 | - |
dc.identifier.issn | 0302-9743 | - |
dc.identifier.issn | 1611-3349 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/65454 | - |
dc.description.abstract | This paper proposes a Flexible Neural Tree (FNT) model for informative gene selection and gene expression profiles classification. Based on the pre-defined instruction/operator sets, a flexible neural tree model can be created and evolved. This framework allows input variables selection, over-layer connections and different activation functions for the various nodes involved. The FNT structure is developed using the Extended Compact Genetic Programming and the free parameters embedded in the neural tree are optimized by particle swarm optimization algorithm. Empirical results on two well-known cancer datasets shows competitive results with existing methods. | - |
dc.format.extent | 8 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | SPRINGER-VERLAG BERLIN | - |
dc.title | Gene expression profiling using flexible neural trees | - |
dc.type | Article | - |
dc.identifier.doi | 10.1007/11875581_133 | - |
dc.identifier.bibliographicCitation | INTELLIGENT DATA ENGINEERING AND AUTOMATED LEARNING - IDEAL 2006, PROCEEDINGS, v.4224, pp 1121 - 1128 | - |
dc.description.isOpenAccess | N | - |
dc.identifier.wosid | 000241790900133 | - |
dc.identifier.scopusid | 2-s2.0-33750539718 | - |
dc.citation.endPage | 1128 | - |
dc.citation.startPage | 1121 | - |
dc.citation.title | INTELLIGENT DATA ENGINEERING AND AUTOMATED LEARNING - IDEAL 2006, PROCEEDINGS | - |
dc.citation.volume | 4224 | - |
dc.type.docType | Article; Proceedings Paper | - |
dc.publisher.location | 독일 | - |
dc.subject.keywordPlus | CLASSIFICATION | - |
dc.subject.keywordPlus | CANCER | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Artificial Intelligence | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Theory & Methods | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
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